Laser-induced fluorescence and Raman spectroscopy are used for the investigation of different genotypes of Thymus daenensis native to the Ilam province of Iran. Different genotypes of $T$. daenensis essential oils, labeled $T_1$ through $T_7$, possess slight differences with regard to the composition of the thymol. The gas chromatography–mass spectrometry (GC–MS) method is performed to determine the concentration of each constituent as a reference method. The Raman spectra of different concentrations of pure thymol dissolved in hexane as standard samples are obtained via a laboratory prototype Raman spectroscopy setup for the calculation of the calibration curve. The regression coefficient and limit of detection are calculated. The possibility of the differentiation of different genotypes of $T$. daenensis is also examined by laser-induced fluorescence spectroscopy, although we do not know the exact amounts of their components. All the fluorescence spectral information is used jointly by cluster analysis to differentiate between 7 genotypes. Our results demonstrate the acceptable precision of Raman spectroscopy with GC–MS and corroborate the capacity of Raman spectroscopy in applications in the quantitative analysis field. Furthermore, the cluster analysis results show that laser-induced fluorescence spectroscopy is an acceptable technique for the rapid classification of different genotypes of $T$. daenensis without having any previous information of their exact amount of constituents. So, the ability to rapidly and nondestructively differentiate between genotypes makes it possible to efficiently select high-quality herbs from many samples.

As a threat to meeting the global demand for food created by the continued growth of population, different methods are being applied to enhance seed germination and plant growth. This study investigates the effect of hydrogen-rich water (HRW) and different plasma-activated waters (PAW) and their combinations including HRW, PAW1, PAW2, HPAW1, and HPAW2 on the seed germination of lentils. Different arc discharge reactors are generated under atmospheric pressure in the air. Optical emission spectroscopy was used to detect the radiative species formed in the plasma zone. Raman spectra and physicochemical properties of different waters were investigated. The results demonstrated significant differences in the properties of different activated waters compared to control water. On day 3 after treatment, the fraction and length of germinated seeds were evaluated. During germination, treated water significantly increased germination parameters such as final germination percentage, mean germination time, germination index, and coefficient of germination velocity. HPAW2 exhibited the highest germination index (GI), which combines germination percentage and speed. The plasma systems also effectively reduced the pH of PAW1 and PAW2, with a greater decrease observed in HPAW1 and HPAW1. Analysis of nitrite and nitrate levels revealed that HPAW2 had the highest concentrations, indicating more reactive processes in the presence of hydrogen. Based on our results, it can be concluded that lentil seed germination can be increased using PAW and hydrogenated PAW combined.

Considering the pivotal role of eggs in the food industry and their nutritional significance, this study employed micro-Raman spectroscopy of eggs, examining both shells and yolks to assess the quality and freshness of eggs. Raman spectra were collected at different temperatures and time intervals to investigate temperature and time effects, potentially indicating Raman peak reduction due to Maillard reaction and oxidation of proteins and lipids and carotenoid depletion, respectively. By calculating the ratio of Raman peaks, lipids, fatty acids, and choline methyl were introduced as biomarkers of temperature and time. Notable correlations were identified between Raman peaks and egg quality coefficients, including egg coefficient and peak 1002 cm$^{-1}$ (protein), total weight and 1301 cm$^{-1}$ (Lipids), yolk weight and 2934 and 3057 cm$^{-1}$, total weight with peak 710 cm$^{-1}$, and egg shape index and peak 3057 cm$^{-1}$. Analysis of eggshells at different time intervals revealed Raman peak reduction during time, demonstrating Raman's effectiveness in assessing egg quality from its shell. Using the PLS-DA method, the classification of eggs at different temperatures and storage times using egg yolk Raman spectra was performed with 80% accuracy, predominantly influenced by carotenoid peaks, showing Raman a practical, and non-destructive method for egg quality and freshness control.